A Poisson regression approach for assessing morbidity risk and determinants among under five children in Nigeria

Idika E Okorie1, Emmanuel Afuecheta2, Saralees Nadarajah3

  • 1Department of Mathematics, Khalifa University, P. O. Box 127788, Abu Dhabi, UAE.

Scientific Reports
|September 16, 2024
PubMed

Insights

This study analyzed under-five child morbidity in Nigeria, finding age, sex, location, and maternal education significantly impact risks of Acute Respiratory Infection (ARI), diarrhea, and fever. Targeted interventions are crucial for vulnerable populations.

Area of Science:

  • Epidemiology
  • Public Health
  • Biostatistics

Background:

  • Childhood morbidity, including Acute Respiratory Infection (ARI), diarrhea, and fever, poses a significant public health challenge in Nigeria.
  • Understanding the determinants of these diseases is crucial for developing effective prevention and control strategies.

Purpose of the Study:

  • To investigate the relationship between background characteristics and under-five morbidity (ARI, diarrhea, fever) in Nigeria.
  • To identify high-risk groups and geographical areas for targeted public health interventions.

Main Methods:

  • Utilized Poisson regression analysis.
  • Employed data from the 2018 Nigeria Demographic and Health Survey (NDHS).
  • Analyzed morbidity patterns based on age, sex, urban/rural residence, and regional/state-level variations.

Main Results:

  • Age, sex, and maternal education were significant predictors of ARI, diarrhea, and fever. For instance, children aged 36-47 months had the highest risk of ARI, while children of mothers with no education had a higher risk of diarrhea and fever.
  • Significant geographical disparities in disease prevalence were observed across different regions and states.
  • Children in urban areas were more likely to suffer from ARI, while rural children had higher risks of diarrhea and fever.

Conclusions:

  • Maternal education and household wealth quintile are significant determinants of under-five morbidity.
  • The findings highlight specific age groups, sexes, and geographical locations that are most vulnerable to ARI, diarrhea, and fever in Nigeria.
  • Results can inform targeted interventions by government and non-governmental agencies to reduce child morbidity.

Related Concept Videos

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
324
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
33
Applications of Life Tables01:22

Applications of Life Tables

Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
56
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
124
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
114
Relative Risk01:12

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
128